Publications

Ventriculostomy, or external ventricular drain (EVD) placement, is frequently performed freehand in urgent bedside settings, resulting in high catheter misplacement rates. Portable augmented reality (AR) guidance offers a low-cost alternative to conventional navigation systems, but mobile and standalone XR hardware impose strict latency, memory, and power constraints. A key enabling component is reliable real-time segmentation…

Accurate compensation of brain deformation is critical for reliable image-guided neurosurgery. Surgical manipulation and tumor resection induce tissue motion, causing preoperative planning images to become misaligned with the intraoperative anatomy. In this systematic review, we examine data-driven methods developed between 2020 and 2025 for brain deformation registration and modeling, with a particular focus on learning-based…

PurposeExternal ventricular drain (EVD) placement is a fundamental neurosurgical procedure for monitoring and relieving elevated intracranial pressure, yet catheter misplacement remains common, particularly during early training. Virtual reality (VR) simulation offers a scalable approach for procedural education. We present VIVIE, a standalone VR-based training system designed to support safe, repeatable practice of EVD placement.MethodsVIVIE simulates…

Stroke remains a leading cause of mortality and disability worldwide, requiring rapid and informed clinical decision-making. A solid spatial understanding of cerebrovascular anatomy and vascular territories in relation to stroke symptoms and severity is critical for timely clinical decision and patient care. However, this knowledge is typically conveyed through static 2D diagrams and printed materials,…

Augmented Reality (AR) tasks that require fine motor control often rely on visual hand representations, yet fully visible hands can introduce occlusion and reduce accuracy. In this work, we investigate adaptive hand visualization techniques that dynamically adjust hand visibility based on the current interaction phase to improve accuracy in AR. We designed an AR-based pedicle…

Artificial intelligence (AI) is increasingly used to support prognosis in Alzheimer's disease (AD), but adoption remains limited due to a lack of transparency and interpretability, particularly for long-term predictions where uncertainty is intrinsic and outcomes may not be known for years. We position uncertainty visualization as an explainable AI (XAI) technique and examine how it…

Surgical AI is no longer a promise on the horizon. Platforms combining robotic assistance, mixed reality navigation, and real-time decision support are entering operating rooms. Yet the values embedded in these systems, the choices about whose data they train on, whose bodies they optimise for, and whose autonomy they quietly override, are rarely considered before…

Hyperspectral imaging (HSI) is a technique that captures and processes information across a wide spectrum of wavelengths, providing detailed spectral data for each pixel in an image to identify and analyze materials or objects. In the surgical domain, it can provide quantitative and qualitative tissue information without the need of any contrast agent, thereby making…

Federated learning (FL) using the federated averaging (FedAvg) algorithm has shown great advantages for large‐scale applications that rely on collaborative learning, especially when the training data is either unbalanced or inaccessible due to privacy constraints. We hypothesize that FedAvg underestimates the full extent of heterogeneity of data when the aggregation is performed. We propose Precision‐Weighted…

MRI-based brain age estimation models aim to assess a subject's biological brain age based on information, such as neuroanatomical features. Various factors, including neurodegenerative diseases, can accelerate brain aging and measuring this phenomena could serve as a potential biomarker for clinical applications. While deep learning (DL)-based regression has recently attracted major attention, existing approaches often…

Pancreatic cancer carries a poor prognosis and relies on endoscopic ultrasound (EUS) for targeted biopsy and radiotherapy. However, the speckle noise, low contrast, and unintuitive appearance of EUS make segmentation of pan-creatic tumors with fully supervised deep learning (DL) models both error-prone and dependent on large, expertcurated annotation datasets. To address these challenges, we present…

Hand visualization significantly impacts user performance in virtual reality (VR), particularly in tasks requiring precise finger movements. Common hand avatar visualizations, such as opaque or transparent, often occlude critical elements or distract users, potentially reducing accuracy. To address this issue, we investigated adaptive hand visibility techniques, which vary the hand avatar visibility based on the…

PurposeVirtual reality (VR) can offer immersive platforms for segmenting complex medical images to facilitate a better understanding of anatomical structures for training, diagnosis, surgical planning, and treatment evaluation. These applications rely on user interaction within the VR environment to manipulate and interpret medical data. However, the optimal interaction schemes and input devices for segmentation tasks…

Routine clinical assessments for Parkinson’s disease are essential instruments in both clinical practice and research, often used to identify disease sub-types and monitor the progression of disease severity. However, each clinic has limited access to information and the quality of these assessments is often degraded by the amount of missing information recorded at the time…

Visualizing 3D medical images is challenging due to self-occlusion, where anatomical structures of interest can be obscured by surrounding tissues. Existing methods, such as slicing and interactive clipping, are limited in their ability to fully represent internal anatomy in context. In contrast, hand-drawn medical illustrations in anatomy books manage occlusion effectively by selectively removing portions…

PurposeImage-guided neurosurgery demands precise depth perception to minimize cognitive burden during intricate navigational tasks. Existing evaluation methods rely heavily on subjective user feedback, which can be biased and inconsistent. This study uses a physiological measure via electroencephalography (EEG), to quantify cognitive load when using novel dynamic depth‐cue visualizations. By comparing dynamic versus static rendering techniques,…

Assessing collateral circulation is essential in determining the best treatment for ischemic stroke patients as good collaterals lead to different treatment options, i.e., thrombectomy, whereas poor collaterals can adversely affect the treatment by leading to excess bleeding and eventually death. To reduce inter- and intra-rater variability and save time in radiologist assessments, computer-aided methods, mainly…

Purpose As a portable and cost‐effective imaging modality with better accessibility than Magnetic Resonance Imaging (MRI), transcranial sonography (TCS) has demonstrated its flexibility and potential utility in various clinical diagnostic applications, including Parkinson's disease and cerebrovascular conditions. To better understand the information in TCS for data analysis and acquisition, MRI can provide guidance for efficient…

Virtual reality (VR) facilitates immersive visualization and interaction with complex medical images in immersive platforms. It remains unclear which VR input schemes and devices are optimal for these tasks. In this study, we perform a 12-person study to investigate user performance and experience while performing medical image segmentation with two control schemes, keyboard and mouse…

Magnetic Resonance Imaging (MRI) examinations are frequently associated with significant anxiety and phobias in patients, negatively impacting imaging quality and patient compliance. In this study, we explore the use of Virtual Reality Exposure Therapy (VRET) to reduce MRI-related anxiety by examining physiological and subjective responses across three virtual scenarios: a 2D video, a 360° video,…

Introduction Decision-making based on AI can be challenging, especially when considering the uncertainty associated with AI predictions. Visualizing uncertainty in AI refers to techniques that use visual cues to represent the level of confidence or uncertainty in an AI model's outputs, such as predictions or decisions. This study aims to investigate the impact of visualizing…

In this work, we present a novel approach to multi-label chest X-ray (CXR) image classification that enhances clinical interpretability while maintaining a streamlined, single-model, single-run training pipeline. Leveraging the CheXpert dataset and VisualCheXbert-derived labels, we incorporate hierarchical label groupings to capture clinically meaningful relationships between diagnoses. To achieve this, we designed a custom hierarchical binary…

Welcome to this special issue of Wiley’s IET Healthcare Technology Letters (HTL) dedicated to the 2024 edition of the augmented environments for computer-assisted interventions (AE-CAI), computer assisted and robotic endoscopy (CARE), and context-aware operating theatres (OR 2.0) joint workshop. We are pleased to present the proceedings of this exciting scientific gathering held in conjunction with…

Global disparities in neurosurgical care necessitate innovations addressing affordability and accuracy, particularly for critical procedures like ventriculostomy. This intervention, vital for managing life‐threatening intracranial pressure increases, is associated with catheter misplacement rates exceeding 30% when using a freehand technique. Such misplacements hold severe consequences including haemorrhage, infection, prolonged hospital stays, and even morbidity and mortality….

Advancements in mixed reality (MR) have led to innovative approaches in image-guided surgery (IGS). In this paper, we provide a comprehensive analysis of the current state of MR in image-guided procedures across various surgical domains. Using the Data Visualization View (DVV) Taxonomy, we analyze the progress made since a 2013 literature review paper on MR…

Video‐assisted thoracic surgery (VATS) is a minimally invasive approach for treating early‐stage non‐small‐cell lung cancer. Optimal trocar placement during VATS ensures comprehensive access to the thoracic cavity, provides a panoramic endoscopic view, and prevents instrument crowding. While established principles such as the Baseball Diamond Principle (BDP) and Triangle Target Principle (TTP) exist, surgeons mainly rely…

BackgroundGaming can serve as an educational tool to allow trainees to practice surgical decision-making in a low-stakes environment. LapBot is a novel free interactive mobile game application that uses artificial intelligence (AI) to provide players with feedback on safe dissection during laparoscopic cholecystectomy (LC). This study aims to provide validity evidence for this mobile game.MethodsTrainees…

Efficient and accurate brain ventricle segmentation from clinical CT scans is critical for emergency surgeries like ventriculostomy. With the challenges in poor soft tissue contrast and a scarcity of well-annotated databases for clinical brain CTs, we introduce a novel uncertainty-aware ventricle segmentation technique without the need of CT segmentation ground truths by leveraging diffusion-model-based domain…

PurposeProper visualization and interaction with complex anatomical data can improve understanding, allowing for more intuitive surgical planning. The goal of our work was to study what the most intuitive yet practical platforms for interacting with 3D medical data are in the context of surgical planning.MethodsWe compared planning using a monitor and mouse, a monitor with…

Recent rising interests in patient-specific thoracic surgical planning and simulation require efficient and robust creation of digital anatomical models from automatic medical image segmentation algorithms. Deep learning (DL) is now state-of-the-art in various radiological tasks, and U-shaped DL models have particularly excelled in medical image segmentation since the inception of the 2D UNet. To date,…

BackgroundVentriculostomy, one of the most common neurosurgical procedures, involves inserting a draining catheter into the brain's ventricular system to alleviate excessive cerebrospinal fluid accumulation. Traditionally, this procedure has relied on freehand techniques guided by anatomical landmarks, which have shown a high rate of misplacement. Recent advancements in virtual reality (VR) and augmented reality (AR) technologies…

Background  Major bile duct injuries during laparoscopic cholecystectomy (LC), often stemming from errors in surgical judgment and visual misperception of critical anatomy, significantly impact morbidity, mortality, disability, and health care costs. Objective  To enhance safe LC learning, we developed an educational mobile game, LapBot Safe Chole, which uses an artificial intelligence (AI) model to provide…

the present technology relates to machine learning (ML) in general and more specifically to methods and systems for providing a global or aggregated machine learning model having been generated by combining models trained on local datasets in a federated learning environment by using parameters indicative of a predictive uncertainty of the models, which also enable…

This study conducts collateral evaluation from ischemic damage using a deep learning-based Siamese network, addressing the challenges associated with a small and imbalanced dataset. The collateral network provides an alternative oxygen and nutrient supply pathway in ischemic stroke cases, influencing treatment decisions. Research in this area focuses on automated collateral assessment using deep learning (DL)…

In this paper, we present a new volumetric ambient occlusion algorithm called Contextual Ambient Occlusion (CAO) that supports real-time clipping. The algorithm produces ambient occlusion images of exactly the same quality as Local Ambient Occlusion (LAO) while enabling real-time modification to the shape used to clip the volume. The main idea of the algorithm is…

Breast cancer is one of the most prevalent forms of cancer, affecting approximately one in eight women during their lifetime. Deciding on breast cancer treatment, which includes the choice between surgical options, frequently demands prompt decision‐making within an 8‐week timeframe. However, many women lack the necessary knowledge and preparation for making informed decisions. Anxiety and…

With more and more availability of both functional Magnetic Resonance Imaging (fMRI) and Diffusion Tensor Imaging (DTI), there is increasing interest and evidence that brain network analysis can enable new possibilities to understand brain function and disease. We have developed an open-source virtual reality (VR) platform, VRNConnect, for exploring brain connectivity data to enable researchers,…

Over the past several years, the satellite workshops and tutorials at MICCAI have experienced increased popularity. This year’s workshop brings together three communities that joined forces for the first time in February 2020 for a MICCAI 2020 Joint Workshop, in light of our common interests in image guidance, navigation and visualization for computer-assisted interventions and…

Eye-strain is a common issue among computer users due to the prolonged periods they spend working in front of digital displays. This can lead to vision problems, such as irritation and tiredness of the eyes and headaches. We propose the Eye-Strain Probation Model (ESPiM), a computational model based on eye-tracking data that measures eye-strain on…

Background One of the bottlenecks of visualization research is the lack of volunteers for studies that evaluate new methods and paradigms. The increased availability of web-based marketplaces, combined with the possibility of implementing volume rendering, a computationally expensive method, on mobile devices, has opened the door for using gamification in the context of medical image…

The virtual hand interaction technique is one of the most common interaction techniques used in virtual reality (VR) systems. A VR application can be designed with different hand visualization styles, which might impact motor dexterity. In this paper, we aim to investigate the effects of three different hand visualization styles — transparent, opaque, and invisible…

Angiography is widely used to detect, diagnose, and treat cerebrovascular diseases. While numerous techniques have been proposed to segment the vascular network from different imaging modalities, deep learning (DL) has emerged as a promising approach. However, existing DL methods often depend on proprietary datasets and extensive manual annotation. Moreover, the availability of pre-trained networks specifically…

How can everyday objects interact or change based on a person’s real-time health status? In the following design case study, we bring together the fields of health and technology with art in the context of diabetic health monitoring. Specifically, we combine smart sock wearable diabetic monitoring technology with home decor (dynamic artwork) as well as…

Freehand ventriculostomy is one of the most common neurosurgical procedures performed when cerebrospinal fluid increases in the ventricular system causing an increase in intracranial pressure. In freehand ventriculostomy, surgeons use anatomical landmarks to determine where to make a burr hole on the skull and insert a catheter inside the brain to drain cerebrospinal fluid. Often,…

While virtual-reality (VR) has shown great promise in radiological tasks, effective user-interaction strategies that can improve efficiency and ergonomics are still under-explored and systematic evaluations of VR interaction techniques in the context of complex anatomical models are rare. Therefore, our study aims to identify the most effective interaction techniques for two common neurosurgical planning tasks…

PurposeCollateral evaluation is typically done using visual inspection of cerebral images and thus suffers from intra- and inter-rater variability. Large open databases of ischemic stroke patients are rare, limiting the use of deep learning methods in treatment decision-making.MethodsWe adapted a pre-trained EfficientNet B0 network through transfer learning to improve collateral evaluation using slice-based and subject-level…

In this paper, we present a new volumetric ambient occlusion algorithm called Contextual Ambient Occlusion (CAO) that supports real-time clipping. The algorithm produces ambient occlusion images of exactly the same quality as Local Ambient Occlusion (LAO) while enabling real-time modification to the shape used to clip the volume. The main idea of the algorithm is…

A lack of multidisciplinary collaboration during the design phase of surgical innovation development often ignores the people whom we are developing for and therefore omits meaningful and relevant user insights that can potentially be gathered about the context-of-use of a product. To mitigate this issue, we propose a user-centered design approach to developing surgical solutions….

In this paper, we evaluate the effect of depth cues on the perception of three-dimensional cerebral angiographic data in a virtual reality (VR) environment. Specifically, a user study was conducted to evaluate the effectiveness of shading, pseudo-chromadepth and aerial perspective, both with and without a dynamic component, where the volume rendering parameters are modified based…

Deep brain stimulation (DBS) is an effective surgical treatment for Parkinson’s disease. The procedure requires precise placement of a stimulation electrode into the therapeutic target while avoiding vital anatomies (e.g. blood vessels) to prevent surgical risks. Therefore, multi-contrast imaging data are often employed to capture full anatomical details for electrode trajectory planning. However, with multiple…

Over the past several years, the satellite workshops and tutorials at MICCAI have experienced increased popularity. This year’s workshop brings together three communities that joined forces for the first time in February 2020 for a MICCAI 2020 Joint Workshop, in light of our common interests in image guidance, navigation and visualisation for computer-assisted interventions. The…

In breast reconstruction after a single mastectomy, the surgeon must choose from hundreds of implants to select the one that best replicates the patient’s natural breast. Due to a lack of measurement tools, the surgeon must depend on their previous experience to visually choose the best implant, leading them to compare and use numerous implants…

The evolution of digitally connected devices and artificial intelligence has opened the door for novel health and fitness applications that can be used by individuals at a time and in an environment convenient to them. The purpose of our research was to develop a platform that requires no additional hardware to provide an online balance…

One of the main challenges of gaze-based interactions is the ability to distinguish normal eye function from a deliberate interaction with the computer system, commonly referred to as ‘Midas touch’. In this paper we propose EyeTAP (Eye tracking point-and-select by Targeted Acoustic Pulse) a contact-free multimodal interaction method for point-and-select tasks. We evaluated the prototype…

Clinical assessments are an integral part of the care and management of Parkinson’s disease, but full spectral assessments are difficult to obtain consistently, especially at follow-up visits. To better understand the etiology and pathogenesis of the disease and to offer accurate prognosis and tailored treatment plans, data-driven computational methods that rely on a large amount…

The evolution of consumer-grade hardware components (e.g., trackers, portable ultrasound probes) has opened the door for the development of low cost systems. We evaluated different low-cost tracking alternatives on the accuracy of 3D freehand ultrasound reconstruction in the context of image-guided neurosurgery. Specifically, we compared two low-cost tracking options, an Intel RealSense depth camera setup…

In this paper, we explore how new technologies can be used to improve Multiple Sclerosis (MS) treatments. Treatment of MS most often includes self-injecting medicine into the subcutis, the tissue layer between the skin and the muscle. The injections can make a patient’s skin sore, red, itchy, and even cause pain, thus many patients suffer…

Augmented Environments for Computer-Assisted Interventions (AECAI), Computer Assisted and Robotic Endoscopy (CARE), and Context-aware Operating Theatres (OR 2.0) workshops. We are pleased to present the proceedings of this exciting scientific gathering held in conjunction with the Medical Image Computing and Computer-Assisted Interventions (MICCAI) conference on October 4th, 2020 as a digital forum. Over the past…

Neuronavigation using preoperative imaging data for neurosurgical guidance is a ubiquitous tool for the planning and resection of oncologic brain disease. These systems are rendered unreliable when brain shift invalidates the patient-image registration. Our previous review in 2015, “Brain shift in neuronavigation of brain tumours: A review” offered a new taxonomy, classification system, and a…

Advances in mobile devices have made possible the adherence to healthy lifestyles and workout routines with less supervision from a professional, for example, a strength trainer or physiotherapist. Mobile health games in particular can help individuals with chronic conditions and disabilities who require physiotherapy and rehabilitation to stay motivated and encouraged during their physiotherapy process….

Fitts’ law is a prediction model to measure the difficulty level of target selection for pointing devices. However, emerging devices and interaction techniques require more flexible parameters to adopt the original Fitts’ law to new circumstances and case scenarios. We propose Index of Difficulty for Eye tracking Applications (IDEA) which integrates Fitts’ law with users’…

Mobile push notifications are a common means to send messages from a mobile application to the user’s device. These messages can have different purposes and may be received at any time of the day in different modalities on a smart device. In this work we seek to answer how to make the most of push…

Assessment of collateral circulation in ischemic stroke, which can identify patients for the most appropriate treatment strategies, is currently conducted with visual inspection by a radiologist. Yet numerous studies have shown that visual inspection suffers from inter and intra-rater variability. We present an automatic evaluation of collaterals using radiomic features and machine learning based on…

PurposeSufficient collateral blood supply is crucial for favorable outcomes with endovascular treatment. The current practice of collateral scoring relies on visual inspection and thus can suffer from inter and intra-rater inconsistency. We present a robust and automatic method to score cerebral collateral blood supply to aid ischemic stroke treatment decision making. The developed method is…

Eye fatigue is a common challenge in eye tracking applications caused by physical and/or mental triggers. Its impact should be analyzed in eye tracking applications, especially for the dwell-time method. As emerging interaction techniques become more sophisticated, their impacts should be analyzed based on various aspects. We propose a novel compound measure for gaze-based interaction…

PurposeNeuronavigation systems making use of augmented reality (AR) have been the focus of much research in the last couple of decades. In recent years, there has been considerable interest in using mobile devices for AR in the operating room (OR). We propose a complete system that performs real-time AR video augmentation on a mobile device…

Stroke is the second leading cause of disability worldwide. In order to minimize disability, the goal of stroke treatment is to preserve tissue in the area where blood supply is decreased but sufficient to stave off cell death. Thrombectomy has been shown to offer fast and efficient reperfusion with high recanalization rates. However, due to…

In breast reconstruction following a single mastectomy, the surgeon needs to choose between tens of available implants to find the one that can reproduce the symmetry of the patient's breasts. However, due to the lack of measurement tools this decision is made purely visually, which means the surgeon has to order multiple implants to confirm…

PurposeThe combination of data visualization and auditory display (e.g., sonification) has been shown to increase accuracy, and reduce perceived difficulty, within 3D navigation tasks. While accuracy within such tasks can be measured in real time, subjective impressions about the difficulty of a task are more elusive to obtain. Prior work utilizing electrophysiology (EEG) has found…

We propose a decentralized conceptual marketplace model for IoT generated personal data. Our model is based on a thorough analysis of personal data in a marketplace context, with specific focus on the challenges presented by commercializing IoT generated personal data. Our model introduces a novel perspective on the commercialization of personal data for a marketplace…

Throughout the history of the Mediterranean region, seafaring and trading played a significant role in the interaction between the cultures and people in the area. In order to engage the general public in learning about maritime cultural heritage we have designed and developed a serious game incorporating geospatially analyzed data from open GIS archaeological maritime…

The work presented in this paper explores the amount of effort, defined by cognitive load, needed to understand depthvisualization while navigating a virtual space in the context of planning for image guided surgery. In this context, cognitiveload is evaluated by measuring brain activity through event-related electroencephalography (EEG). We found a significantdifference between dynamic depth cue…

Guest Editorial: Papers from the 13th Workshop on Augmented Environments for Computer Assisted Interventions – PMC Skip to main content Here's how you know Official websites use .gov A .gov website belongs to an official government organization in the United States. Secure .gov websites use HTTPS A lock ( Locked padlock icon ) or https://…

User interaction has the potential to greatly facilitate the exploration and understanding of 3D medical images for diagnosis and treatment. However, in certain specialized environments such as in an operating room (OR), technical and physical constraints such as the need to enforce strict sterility rules, make interaction challenging. In this paper, we propose to facilitate…

Ultrasound (US) is a popular medical imaging technique in the clinic due to its low cost, high portability, and real-time diagnostic value. A special type of ultrasound technique, transcranial Doppler (TCD) ultrasound can be used to measure blood flows in cerebral blood vessels through acoustic bone windows of the intact human skull. Although TCD ultrasound…

The goal of augmented reality (AR) in image-guided interventions is to allow surgeons to access navigation information during a procedure without shifting their attention away from the operative field. To be effective, augmentation should provide the right information at the right time, avoid distracting the surgeons, and provide an unambiguous and perceptually sound representation of…

Guest Editorial: Papers from the 12th Workshop on Augmented Environments for Computer-Assisted Interventions – PMC Skip to main content Here's how you know Official websites use .gov A .gov website belongs to an official government organization in the United States. Secure .gov websites use HTTPS A lock ( Locked padlock icon ) or https:// means…

In image‐guided neurosurgery, a registration between the patient and their pre‐operative images and the tracking of surgical tools enables GPS‐like guidance to the surgeon. However, factors such as brainshift, image distortion, and registration error cause the patient‐to‐image alignment accuracy to degrade throughout the surgical procedure no longer providing accurate guidance. The authors present a gesture‐based…

Recent developments pertaining to ear-mounted wearable computer interfaces (i.e., “hearables”) offer a number of distinct affordances over other wearable devices in ambient and ubiquitous computing systems. This paper provides a survey of hearables and the possibilities that they offer as computer interfaces. Thereafter, these affordances are examined with respect to other wearable interfaces. Finally, several…

We present our work investigating the feasibility of combining intraoperative ultrasound for brain shift correction and augmented reality (AR) visualization for intraoperative interpretation of patient-specific models in image-guided neurosurgery (IGNS) of brain tumors. We combine two imaging technologies for image-guided brain tumor neurosurgery. Throughout surgical interventions, AR was used to assess different surgical strategies using…

Guest Editors' Foreword: Special Issue on Augmented Environments for Computer-Assisted Interventions Page 1 149 Welcome to this Special Issue of the IET journal Healthcare Technology Letters (HTL) dedicated to the 11th edition of the International Workshop on Augmented Environments for Computer-Assisted Interventions (AE-CAI). We are pleased to present the proceedings of this exciting scientific gathering…

Guest Editors' Foreword: Special Issue on Augmented Environments for Computer-Assisted Interventions: CAI systems enable more precise, safer, and less invasive interventional treatments – PMC Skip to main content Here's how you know Official websites use .gov A .gov website belongs to an official government organization in the United States. Secure .gov websites use HTTPS A…

Image‐guided neurosurgery, or neuronavigation, has been used to visualise the location of a surgical probe by mapping the probe location to pre‐operative models of a patient's anatomy. One common limitation of this approach is that it requires the surgeon to divert their attention away from the patient and towards the neuronavigation system. In order to…

Image‐guided surgery (IGS) has allowed for more minimally invasive procedures, leading to better patient outcomes, reduced risk of infection, less pain, shorter hospital stays and faster recoveries. One drawback that has emerged with IGS is that the surgeon must shift their attention from the patient to the monitor for guidance. Yet both cognitive and motor…

Stroke is the second leading cause of disability worldwide. Thrombectomy has been shown to offer fast and efficient reperfusion with high recanalization rates and thus improved patient outcomes. One of the most important indicators to identify patients amenable to thrombectomy is evidence of good collateral circulation. Currently, methods for evaluating collateral circulation are generally limited…

PurposeNavigation systems commonly used in neurosurgery suffer from two main drawbacks: (1) their accuracy degrades over the course of the operation and (2) they require the surgeon to mentally map images from the monitor to the patient. In this paper, we introduce the Intraoperative Brain Imaging System (IBIS), an open-source image-guided neurosurgery research platform that…

Purpose: Neuronavigation based on preoperative imaging data is a ubiquitous tool for image guidance in neurosurgery. However, it is rendered unreliable when brain shift invalidates the patient-to-image registration. Many investigators have tried to explain, quantify, and compensate for this phenomenon to allow extended use of neuronavigation systems for the duration of surgery. The purpose of…

One of the main challenges facing members of the medical imaging community is the lack of real clinical cases and ground truth datasets with which to validate new registration, segmentation, and other image processing algorithms. In this work we present a collection of data from tumour patients acquired at the Montreal Neurological Institute and Hospital…

Augmented reality has been proposed as a solution to overcome some of the current shortcomings of image-guided neurosurgery. In particular, it has been used to merge patient images, surgical plans, and the surgical field of view into a comprehensive visualization. In this paper we explore the use of augmented reality for planning craniotomies in image-guided…

PurposeThe aim of this report is to present a prototype augmented reality (AR) intra-operative brain imaging system. We present our experience of using this new neuronavigation system in neurovascular surgery and discuss the feasibility of this technology for aneurysms, arteriovenous malformations (AVMs), and arteriovenous fistulae (AVFs).MethodsWe developed an augmented reality system that uses an external…

In image-guided neurosurgery the patient is registered with the reference of a tracking system and preoperative data before sterile draping. Due to several factors extensively reported in the literature, the accuracy of this registration can be much deteriorated after the initial phases of the surgery. In this paper, we present a simple method that allows…

Augmented reality has the potential to aid surgeons with particular surgical tasks in image-guided surgery. In augmented reality (AR) visualization for neurosurgery, the live view of the surgical scene is merged with preoperative patient data, aiding the surgeon in mapping patient images from the image-guidance system to the real patient. Furthermore, augmented reality visualization allows…

We present our work to combine intraoperative ultrasound imaging and augmented reality visualization to improve the use of patient specific models throughout image-guided neurosurgery in the context of tumour resections. Preliminary results in a study of 3 patients demonstrate the successful combination of the two technologies as well as improved accuracy of the patient-specific models…

Image-guided surgery (IGS), a form of minimally invasive computer-assisted surgery, was first used in the field of neurosurgery in the mid-1990s. Since then, IGS has gained wide acceptance and is used in numerous other surgical domains having shown improvements in patient outcomes with lower morbidity and mortality rates, smaller incisions and reduced trauma to the…

In neurovascular surgery, the surgeon must navigate among eloquent areas, through complex neurovascular anatomy to a particular vascular malformation or anomaly. Augmented reality (AR) visualization may be used to show vessels not visible when looking at the brain surface and to aid navigation by bringing into spatial alignment pre-operative vascular data with the real patient…

Image-guided surgery correlates pre-operative diagnostic patient images with the patient on the operating room table by using a patient-to-image registration and localizing and tracking the patient and the surgical instruments. The task of spatially aligning the patient with the diagnostic images into one view remains, however, with the surgeon. This task is not trivial, is…

Cerebral vascular images obtained through angiography are used by neurosurgeons for diagnosis, surgical planning, and intraoperative guidance. The intricate branching of the vessels and furcations, however, make the task of understanding the spatial three-dimensional layout of these images challenging. In this paper, we present empirical studies on the effect of different perceptual cues (fog, pseudo-chromadepth,…